Use of Genome-Wide Expression Data to Mine the “Gray Zone” of GWA Studies Leads to Novel Candidate Obesity Genes
Open accessAbstract
To get beyond the "low-hanging fruits" so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we describe a novel integrative method for complex disease gene identification utilizing both genome-wide transcript profiling of adipose tissue samples and consequent analysis of genome-wide association data generated in large SNP scans. We infer causality of genes with obesity by employing a unique set of monozygotic twin pairs discordant for BMI (n = 13 pairs, age 24-28 years, 15.4 kg mean weight difference) and contrast the transcript profiles with those from a larger sample of non-related adult individuals (N = 77). Using this approach, we were able to identify 27 genes with possibly causal roles in determining the degree of human adiposity. Testing for association of SNP variants in these 27 genes in the population samples of the large ENGAGE consortium (N = 21,000) revealed a significant deviation of P-values from the expected (P = 4x10(-4)). A total of 13 genes contained SNPs nominally associated with BMI. The top finding was blood coagulation factor F13A1 identified as a novel obesity gene also replicated in a second GWA set of approximately 2,000 individuals. This study presents a new approach to utilizing gene expression studies for informing choice of candidate genes for complex human phenotypes, such as obesity.
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If multiple GWAS hits exist in the same module, their cumulative presence can significantly contribute to disease development.
“If multiple Genome-Wide Association Study (GWAS) hits exist in the same module, their cumulative presence can significantly contribute to disease development [120, 163, 164].”
From Gene co-expression analysis for functional classification and gene–disease predictions (2017) · cites this paper as [163]
The Results section, “Mining the ENGAGE consortium GWA data” (page unavailable), reports multiple BMI-associated SNPs among genes considered putatively causal and a significant excess of small P-values across that gene set. It does not establish that the hits occur in the same module or that their cumulative presence significantly contributes to disease development. (LLM, conf=0.78)
Experimental — accuracy not yet measuredThe explained BMI variance is unlikely to improve with larger samples due to complex biological-environmental interactions.
“However, these 32 loci explained only 1.5% of the BMI variance (1,2), a situation that is unlikely to improve with larger samples because of the complex interactions between biological and environmental factors.”
From The Addictive Dimensionality of Obesity (2013) · cites this paper as [1]
Those 32 loci explained only 1.5% of BMI variance.
“However, these 32 loci explained only 1.5% of the BMI variance (1,2), a situation that is unlikely to improve with larger samples because of the complex interactions between biological and environmental factors.”
From The Addictive Dimensionality of Obesity (2013) · cites this paper as [1]
A GWAS of 249,796 individuals of European descent identified 32 loci associated with BMI.
“Indeed, the most recent whole genome-wide association study conducted in 249,796 individuals of European descent identified 32 loci associated with body mass index (BMI).”
From The Addictive Dimensionality of Obesity (2013) · cites this paper as [1]
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- Authors
- Naukkarinen, J., Surakka, I., Pietiläinen, K. H., Rissanen, A., Salomaa, V., Ripatti, S., Yki-Järvinen, H., van Duijn, C. M., Wichmann, H.-E., Kaprio, J., Taskinen, M.-R., Peltonen, L., & ENGAGE Consortium
- Affiliations
- University of Helsinki (FI)
- Finnish Institute for Health and Welfare (FI)
- Helmholtz Munich (DE)
- Helsinki University Hospital (FI)
- Broad Institute (US)
- Corresponding author
- Naukkarinen, Jussi
- ORCID
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- PLoS Genetics
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- Published
- 2010-06-03
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- 6
- Issue
- 6
- Pages
- e1000976
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- PMC
- PMC2880558
- OpenAlex
- W1493450043
- Cited by
- 0
- References
- 33
- FWCI
- 0.00
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- Language
- en
- Open access
- gold
- doi.org
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- Helsingin Yliopisto
- Helsingin ja Uudenmaan Sairaanhoitopiiri
- Jalmari ja Rauha Ahokkaan Säätiö
- Wellcome Trust (FP7/2007–2013, 01254, 129494)
- European Molecular Biology Laboratory
- Royal Society
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- King's College London
- University of Oxford
- European Commission (018947, LSHG-CT-2006-01947, 2007–2013, FP7 2007-2013, 201413, 480-04-004, FP7/2007, 01254)
- Universiteit Leiden (10‐000‐1002)
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- Vrije Universiteit Amsterdam (FP7/2007-2013)
- Academy of Finland (129494)
- Bundesministerium für Bildung und Forschung
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (10-000-1002, 904-61-090, FP7 2007-2013, NWO 480-04-004, 56‐464‐14192, 175.010.200, 175.010.2005.011, Spi-56-464-14192, 14192, 480-04-004)
- Lunds Universitet
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- Sydäntutkimussäätiö
- Tartu Ülikool
- Centre for Medical Systems Biology (480-04-004)
- Provincia autonoma di Bolzano - Alto Adige
- National Institutes of Health (FP7/2007-2013, 6r01hl087679-03, NWO 480-04-004, EU/QLRT-2001-01254)
- Medical Research Council (FP7/20072013)
- Erasmus Universitair Medisch Centrum Rotterdam
- Münchner Zentrum für Gesundheitswissenschaften
- Norwegian Institute of Public Health
- National Heart, Lung, and Blood Institute (5R01 HL087679-02, 5R01HL087679, R01 HL087679)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- obesity, monozygotic twin discordance, body mass index, adipose tissue gene expression, transcriptome, genome-wide association study, F13A1
- MeSH terms
- Adult, Biopsy, Gene Expression Regulation, Humans, Obesity, Body Mass Index, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Young Adult
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